A novel time-domain signal processing algorithm for real time ventricular fibrillation detection

Autores
Monte, Gustavo; Scarone, Norberto; Liscovsky, Pablo
Año de publicación
2011
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This paper presents an application of a novel algorithm for real time detection of ECG pathologies, especially ventricular fibrillation. It is based on segmentation and labeling process of an oversampled signal. After this treatment, analyzing sequence of segments, global signal behaviours are obtained in the same way like a human being does. The entire process can be seen as a morphological filtering after a smart data sampling. The algorithm does not require any ECG digital signal pre-processing, and the computational cost is low, so it can be embedded into the sensors for wearable and permanent applications. The proposed algorithms could be the input signal description to expert systems or to artificial intelligence software in order to detect other pathologies
Fil: Gustavo Monte - Universidad Tecnológica Nacional Facultad Regional del Neuquèn
Fil: Scarone Norberto . Universidad Tecnológica Nacional Facultad Regional del Neuquèn
Fil: Liscovsky Pablo. Universidad Tecnológica Nacional Facultad Regional del Neuquèn
Peer Reviewed
Materia
signal segmentation- smart sampling-ecg signal processing
Nivel de accesibilidad
acceso abierto
Condiciones de uso
2020-02-18T22:55:17Z
Repositorio
Repositorio Institucional Abierto (UTN)
Institución
Universidad Tecnológica Nacional
OAI Identificador
oai:ria.utn.edu.ar:20.500.12272/4305
Acceder
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network_acronym_str RIAUTN
repository_id_str a
network_name_str Repositorio Institucional Abierto (UTN)
spelling A novel time-domain signal processing algorithm for real time ventricular fibrillation detectionMonte, GustavoScarone, NorbertoLiscovsky, Pablosignal segmentation- smart sampling-ecg signal processingThis paper presents an application of a novel algorithm for real time detection of ECG pathologies, especially ventricular fibrillation. It is based on segmentation and labeling process of an oversampled signal. After this treatment, analyzing sequence of segments, global signal behaviours are obtained in the same way like a human being does. The entire process can be seen as a morphological filtering after a smart data sampling. The algorithm does not require any ECG digital signal pre-processing, and the computational cost is low, so it can be embedded into the sensors for wearable and permanent applications. The proposed algorithms could be the input signal description to expert systems or to artificial intelligence software in order to detect other pathologiesFil: Gustavo Monte - Universidad Tecnológica Nacional Facultad Regional del NeuquènFil: Scarone Norberto . Universidad Tecnológica Nacional Facultad Regional del NeuquènFil: Liscovsky Pablo. Universidad Tecnológica Nacional Facultad Regional del NeuquènPeer Reviewed2020-02-18T22:55:17Z2020-02-18T22:55:17Z2011-12-23info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/20.500.12272/430510.1088/1742-6596/332/1/012015engenginfo:eu-repo/semantics/openAccess2020-02-18T22:55:17Zhttp://creativecommons.org/licenses/by-nc-nd/4.0/Monte Gustavocreative commosAttribution-NonCommercial-NoDerivatives 4.0 Internacional2011-12-23reponame:Repositorio Institucional Abierto (UTN)instname:Universidad Tecnológica Nacional2026-09-24T12:43:50Zoai:ria.utn.edu.ar:20.500.12272/4305instacron:UTNInstitucionalhttp://ria.utn.edu.ar/Universidad públicaNo correspondehttp://ria.utn.edu.ar/oaigestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:a2026-09-24 12:43:52.05Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacionalfalse
dc.title.none.fl_str_mv A novel time-domain signal processing algorithm for real time ventricular fibrillation detection
title A novel time-domain signal processing algorithm for real time ventricular fibrillation detection
spellingShingle A novel time-domain signal processing algorithm for real time ventricular fibrillation detection
Monte, Gustavo
signal segmentation- smart sampling-ecg signal processing
title_short A novel time-domain signal processing algorithm for real time ventricular fibrillation detection
title_full A novel time-domain signal processing algorithm for real time ventricular fibrillation detection
title_fullStr A novel time-domain signal processing algorithm for real time ventricular fibrillation detection
title_full_unstemmed A novel time-domain signal processing algorithm for real time ventricular fibrillation detection
title_sort A novel time-domain signal processing algorithm for real time ventricular fibrillation detection
dc.creator.none.fl_str_mv Monte, Gustavo
Scarone, Norberto
Liscovsky, Pablo
author Monte, Gustavo
author_facet Monte, Gustavo
Scarone, Norberto
Liscovsky, Pablo
author_role author
author2 Scarone, Norberto
Liscovsky, Pablo
author2_role author
author
dc.subject.none.fl_str_mv signal segmentation- smart sampling-ecg signal processing
topic signal segmentation- smart sampling-ecg signal processing
dc.description.none.fl_txt_mv This paper presents an application of a novel algorithm for real time detection of ECG pathologies, especially ventricular fibrillation. It is based on segmentation and labeling process of an oversampled signal. After this treatment, analyzing sequence of segments, global signal behaviours are obtained in the same way like a human being does. The entire process can be seen as a morphological filtering after a smart data sampling. The algorithm does not require any ECG digital signal pre-processing, and the computational cost is low, so it can be embedded into the sensors for wearable and permanent applications. The proposed algorithms could be the input signal description to expert systems or to artificial intelligence software in order to detect other pathologies
Fil: Gustavo Monte - Universidad Tecnológica Nacional Facultad Regional del Neuquèn
Fil: Scarone Norberto . Universidad Tecnológica Nacional Facultad Regional del Neuquèn
Fil: Liscovsky Pablo. Universidad Tecnológica Nacional Facultad Regional del Neuquèn
Peer Reviewed
description This paper presents an application of a novel algorithm for real time detection of ECG pathologies, especially ventricular fibrillation. It is based on segmentation and labeling process of an oversampled signal. After this treatment, analyzing sequence of segments, global signal behaviours are obtained in the same way like a human being does. The entire process can be seen as a morphological filtering after a smart data sampling. The algorithm does not require any ECG digital signal pre-processing, and the computational cost is low, so it can be embedded into the sensors for wearable and permanent applications. The proposed algorithms could be the input signal description to expert systems or to artificial intelligence software in order to detect other pathologies
publishDate 2011
dc.date.none.fl_str_mv 2011-12-23
2020-02-18T22:55:17Z
2020-02-18T22:55:17Z
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12272/4305
10.1088/1742-6596/332/1/012015
url http://hdl.handle.net/20.500.12272/4305
identifier_str_mv 10.1088/1742-6596/332/1/012015
dc.language.none.fl_str_mv eng
eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
2020-02-18T22:55:17Z
http://creativecommons.org/licenses/by-nc-nd/4.0/
Monte Gustavo
creative commos
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
2011-12-23
eu_rights_str_mv openAccess
rights_invalid_str_mv 2020-02-18T22:55:17Z
http://creativecommons.org/licenses/by-nc-nd/4.0/
Monte Gustavo
creative commos
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
2011-12-23
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.source.none.fl_str_mv reponame:Repositorio Institucional Abierto (UTN)
instname:Universidad Tecnológica Nacional
reponame_str Repositorio Institucional Abierto (UTN)
collection Repositorio Institucional Abierto (UTN)
instname_str Universidad Tecnológica Nacional
repository.name.fl_str_mv Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacional
repository.mail.fl_str_mv gestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.ar
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score 13.265058

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